MORPHOLOGY OF DRAINED UPLAND DEPRESSIONS ON THE DES MOINES LOBE OF IOWA

There is growing interest in understanding the roles that drained wetland depressions, known as prairie potholes, have on regional and sub-regional stream flows, and in implementing wetland restorations, specifically within the Iowa Des Moines Lobe (DML-IA) portion of the Prairie Pothole Region (PPR). Critical information regarding the morphology and spatial distribution of depressions at the regional and sub-regional scales is provided by topographic data derived from Light Detection and Ranging (LiDAR) surveys, allowing for the determination of depressional morphology to be measured more quickly and accurately compared to manual or photogrammetric surveys.

We developed an algorithm (the Surface Depression Morphology Tool – SDMT) which quickly and accurately identifies, delineates, and derives the morphology for all drained depressions within any Digital Elevation Model (DEM), which we ran on 3 m hydrologically corrected DEMs comprising the entire DML-IA. The algorithm used in the SDMT is simpler and more computationally efficient than integration over triangular irregular networks (TINs) used by other algorithms.

189,130 upland depressional features were found, after automatic and manual filtering of the dataset. The cumulative upland depressional area was found to be 6.4% of the total land surface of the DML-IA. Frequencies of maximum area (A_max) and maximum volume (V_max) were found to be reasonably described by a power-law distribution, however maximum depth (H_max) was only marginally described by a power-law distribution. In general, depressions existing in the Algona Advance glacial sub-region tend to be larger and have greater storage capacity than the other glacial sub-regions of the DML-IA.

Overall, maximum depressional inundation areas, volumes, and depths were identified to be power-law distributed, with most depressional basins being generally small and shallow. This is in contrast to other areas of the Prairie Pothole Region (PPR) which tend to have smaller but deeper depressional basins. Nearly 78% of the upland depressions on the DML-IA are less than 1 ha in size, demonstrating the high prevalence of small depressional basins. The dataset developed may prove useful in efforts to identify and restore depressional wetlands within the DML-IA.